A two-stage robust optimization approach for the berth allocation problem under uncertainty

This paper examines the berth allocation problem under uncertainty. We use uncertainty sets to describe the possible scenarios without depending on probabilistic information. Then we adopt a two-stage robust optimization approach where baseline schedule is made before and the recovery operation is made after the disruptions are known. Three two-stage robust models are constructed to generate less conservative solutions. Experimental results demonstrate that the schedule's robustness can be improved with only a slight increase in the baseline cost. Finally, some management insights are presented based on the numerical results.